Although proteins are translated on cytoplasmic ribosomes, many of these proteins play essential roles in the nucleus, mediating key cellular processes including but not limited to DNA replication and repair as well as transcription and RNA processing. Thus, understanding how these critical nuclear proteins are accurately targeted to the nucleus is of paramount importance in biology. Interaction and structural studies in the recent years have jointly revealed some general rules on the specificity determinants of the recognition of nuclear targeting signals by their specific receptors, at least for two nuclear import pathways: (i) the classical pathway, which involves the classical nuclear localization sequences (cNLSs) and the receptors importin-α/karyopherin-α and importin-β/karyopherin-β1; and (ii) the karyopherin-β2 pathway, which employs the proline-tyrosine (PY)-NLSs and the receptor transportin-1/karyopherin-β2. The understanding of specificity rules allows the prediction of protein nuclear localization. We review the current understanding of the molecular determinants of the specificity of nuclear import, focusing on the importin-α•cargo recognition, as well as the currently available databases and predictive tools relevant to nuclear localization. This article is part of a Special Issue entitled: Regulation of Signaling and Cellular Fate through Modulation of Nuclear Protein Import.

BackgroundCD4+ T-cell epitopes play a crucial role in eliciting vigorous protective immune responses during peptide (epitope)-based vaccination. The prediction of these epitopes focuses on the peptide binding process by MHC class II proteins. The ability to account for MHC class II polymorphism is critical for epitope-based vaccine design tools, as different allelic variants can have different peptide repertoires. In addition, the specificity of CD4+ T-cells is often directed to a very limited set of immunodominant peptides in pathogen proteins. The ability to predict what epitopes are most likely to dominate an immune response remains a challenge.ResultsWe developed the computational tool Predivac to predict CD4+ T-cell epitopes. Predivac can make predictions for 95% of all MHC class II protein variants (allotypes), a substantial advance over other available methods. Predivac bases its prediction on the concept of specificity-determining residues. The performance of the method was assessed both for high-affinity HLA class II peptide binding and CD4+ T-cell epitope prediction. In terms of epitope prediction, Predivac outperformed three available pan-specific approaches (delivering the highest specificity). A central finding was the high accuracy delivered by the method in the identification of immunodominant and promiscuous CD4+ T-cell epitopes, which play an essential role in epitope-based vaccine design.ConclusionsThe comprehensive HLA class II allele coverage along with the high specificity in identifying immunodominant CD4+ T-cell epitopes makes Predivac a valuable tool to aid epitope-based vaccine design in the context of a genetically heterogeneous human population.The tool is available at: http://predivac.biosci.uq.edu.au/.

Objective We undertook this study to evaluate the activation and functional relevance of inflammasome pathways in ankylosing spondylitis (AS) patients and rodent models and their relationship to dysbiosis. Methods An inflammasome pathway was evaluated in the gut and peripheral blood from 40 AS patients using quantitative reverse transcriptase–polymerase chain reaction (qRT‐PCR), immunohistochemistry (IHC), flow cytometry, and confocal microscopy, and was compared to that of 20 healthy controls and 10 patients with Crohn’s disease. Bacteria was visualized using silver stain in human samples, and antibiotics were administered to HLA–B27–transgenic rats. The NLRP3 inhibitor MCC950 was administered to SKG mice, and ileal and joint tissues were assessed by IHC analysis and real‐time qRT‐PCR. The role of inflammasome in modulating the interleukin‐23 (IL‐23)/IL‐17 axis was studied ex vivo. Results Expression levels of Nlrp3, Nlrc4, and Aim2 were increased in the gut of HLA–B27–transgenic rats and reduced by antibiotic treatment (P < 0.05). In curdlan‐treated SKG mice, NLRP3 blockade prevented ileitis and delayed arthritis onset (P < 0.05). Compared to healthy controls, AS patients demonstrated overexpression of NLRP3 (fold induction 2.33 versus 22.2; P < 0.001), NLRC4 (fold induction 1.90 versus 6.47; P < 0.001), AIM2 (fold induction 2.40 versus 20.8; P < 0.001), CASP1 (fold induction 2.53 versus 24.8; P < 0.001), IL1B (fold induction 1.07 versus 10.93; P < 0.001), and IL18 (fold induction 2.56 versus 15.67; P < 0.001) in the ileum, and caspase 1 activity was increased (P < 0.01). The score of adherent and invasive mucosa‐associated bacteria was higher in AS (P < 0.01) and correlated with the expression of inflammasome components in peripheral blood mononuclear cells (P < 0.001). NLRP3 expression was associated with disease activity (the Ankylosing Spondylitis Disease Activity Score using the C‐reactive protein level) (r2 = 0.28, P < 0.01) and with IL23A expression (r2 = 0.34, P < 0.001). In vitro, inflammasome activation in AS monocytes was paralleled by increased serum levels of IL‐1β and IL‐18. Induction of IL23A, IL17A, and IL22 was IL‐1β–dependent. Conclusion Inflammasome activation occurs in rodent models of AS and in AS patients, is associated with dysbiosis, and is involved in triggering ileitis in SKG mice. Inflammasomes drive type III cytokine production with an IL‐1β–dependent mechanism in AS patients.

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Many protein-RNA recognition events are known to exhibit conformational changes from qualitative observations of individual complexes. However, a quantitative estimation of conformational changes is required if protein-RNA docking and template-based methods for RNA binding site prediction are to be developed. This study presents the first quantitative evaluation of conformational changes that occur when proteins bind RNA. The analysis of twelve RNA-binding proteins in the bound and unbound states using error-scaled difference distance matrices is presented. The binding site residues are mapped to each structure, and the conformational changes that affect these residues are evaluated. Of the twelve proteins four exhibit greater movements in nonbinding site residues, and a further four show the greatest movements in binding site residues. The remaining four proteins display no significant conformational change. When interface residues are found to be in conformationally variable regions of the protein they are typically seen to move less than 2 A between the bound and unbound conformations. The current data indicate that conformational changes in the binding site residues of RNA binding proteins may not be as significant as previously suggested, but a larger data set is required before wider conclusions may be drawn. The implications of the observed conformational changes for protein function prediction are discussed.